Kubicle

Generative AI is reshaping how non-technical professionals contribute to software and workflow development. Kubicle’s new course, Inline Coding with AI, introduces the concept of “Vibe Coding”—a practical approach to building applications and automation using AI chat tools directly within coding environments.

This course empowers business professionals to engage in technical problem-solving, prototype digital tools, and streamline workflows—without requiring deep programming expertise.

Course Overview: Inline Coding with AI
Learners will gain hands-on experience planning, prompting, and iterating on real AI-generated applications—from client-facing tools to automated internal workflows. The course also covers coding environments, debugging, AI model selection, and responsible use of AI coding platforms.

Included Lessons:

• Introduction to Coding Concepts
  Explains the value of coding literacy for professionals in decision-making, communication, and innovation.
• Defining Vibe Coding
  Introduces the core concept and realistic expectations around using AI to write functional code inline.
• The Vibe Coder Mindset
  Presents a product-oriented approach to AI coding, focusing on clarity, purpose, and user outcomes.
• Selecting Appropriate Tech Stacks
  Outlines how to choose technologies that suit project needs and the capabilities of AI tools.
• Using a Product Requirement Document
  Introduces documentation practices that enhance the precision and success of AI-generated code.
• Inline AI Coding Environments
  Explores tools and platforms that support embedded coding experiences, along with their pros and cons.
• Case Studies: Planning and Building Projects
  Walks through the development of multiple small-scale apps, from concept to iteration.
• Debugging and Error Resolution
  Covers common troubleshooting methods and techniques to maintain code quality.
• Effective Feature Requests
  Shares best practices for communicating with AI tools to guide functionality and iteration.
• Workflow Automation Projects
  Demonstrates how to build and refine tools that automate repetitive tasks and improve efficiency.
• Managing Limitations and Constraints
  Provides strategies for working around technical limitations in inline environments.
• Interactive Dashboard Projects
  Covers the design and development of advanced data dashboards with interactive elements.
• Managing Extended Iterations
  Explains how to maintain project continuity across sessions and avoid AI context loss.
• Selecting AI Models
  Reviews how to assess and select AI tools, including considerations for performance and updates.
• Security and Compliance Considerations
  Outlines key legal and ethical requirements when using AI to build software or process data.

Key Outcomes:
By the end of this course, learners will be able to:

• Understand and apply Vibe Coding methods using AI-powered coding environments
• Plan and build functional tools through structured prompting and iteration
• Troubleshoot errors and guide AI through development processes
• Automate simple workflows and visualize data with interactive dashboards
• Evaluate AI tools for business needs while addressing compliance and security considerations

This course is ideal for cross-functional professionals and teams exploring AI-enhanced workflows, internal tooling, or low-code software development.

As AI adoption grows across all areas of business, so do the ethical challenges that come with it. Kubicle’s new course, AI Ethics and the Workplace, helps learners understand how to use AI responsibly by exploring core ethical principles and practical frameworks for evaluation, oversight, and decision-making.

This course is designed to build awareness and promote accountability in the use of AI tools—across teams, processes, and procurement.

Course Overview: AI Ethics and the Workplace
The course introduces learners to six core principles of ethical AI—transparency, accountability, fairness, privacy, reliability and safety, and beneficence—and shows how these can be applied in everyday workplace scenarios. It supports critical thinking, risk recognition, and values-based implementation.

Included Lessons:

• Introduction to AI Ethics and the Workplace
  Defines AI in the workplace and outlines why ethical use is a growing concern for organizations and individuals.
• The Pillars of Trustworthy AI
  Introduces a six-pillar ethical framework for evaluating and managing AI use.
• Building Ethical AI Practices through Values
  Links ethical AI use to organizational values and culture, supporting trust and alignment.
• When Speed Overrides Ethics
  Explores how performance-driven decisions can compromise fairness and integrity.
• Who’s Accountable when AI Fails?
  Highlights the importance of clear oversight and accountability structures.
• Understanding Ethical Risks in AI
  Identifies common risks such as bias, privacy invasion, and systemic exclusion.
• Uncovering Bias in Algorithms
  Explains how training data and design choices can lead to discriminatory outcomes.
• Transparency and Explainability
  Emphasizes the need to understand and communicate how AI systems make decisions.
• Data, Privacy, and Consent
  Focuses on the ethical management of user data and the role of consent in responsible AI.
• Ethical AI in Content and Communication
  Addresses risks associated with AI-generated content and communication.
• Hallucinations, Hidden Logic, and Exclusion
  Covers the risk of AI misinformation, hidden logic, and the exclusion of diverse voices.
• Spotting the Red Flags Early
  Provides techniques for early detection of problematic AI behaviors or use cases.
• Asking the Right Questions
  Introduces a questioning mindset to guide ethical evaluations of AI tools.
• Evaluating AI Tools and Vendors
  Applies ethical criteria to vendor selection and procurement decisions.

Key Outcomes:
By the end of this course, learners will be able to:

• Apply ethical principles to evaluate AI tools and workplace practices
• Identify common risks such as bias, exclusion, and misinformation
• Understand the importance of transparency, accountability, and data protection
• Recognize early warning signs of unethical AI behavior
• Support values-based procurement and implementation decisions

This course is ideal for teams adopting or scaling AI tools and for organizations building responsible AI practices into governance, procurement, and training.

We’re excited to launch a brand-new course that empowers learners to build intelligent, no-code AI agents using Microsoft Copilot Studio. Whether you're in IT, operations, or any role looking to automate and enhance everyday workflows, this course will help you design, build, and deploy Copilots that deliver real business value.

New Course: Introduction to Copilot Studio
Learn how to create powerful, AI-driven Copilots without writing a single line of code. This course explores how generative AI transforms task automation, and walks you through building a fully functional HR Copilot using topics, actions, and custom knowledge sources.

What’s included?

• Introduction to Copilots
  Understand how AI Copilots differ from traditional chatbots—and how they support smarter business interactions.
• Exploring Copilot Studio’s Capabilities
  Discover how Copilots connect with enterprise systems to automate and assist with real-time decisions.
• Generative AI in Microsoft Copilot Studio
  Learn how Copilot Studio uses generative AI to deliver dynamic responses and manage fallback behavior.
• Building Our First Copilot
  Step-by-step guidance to build your first Copilot using Microsoft’s intuitive no-code interface.
• Adding Knowledge Sources to Help Our Agent
  Use documents and custom data to enhance your Copilot’s intelligence while minimizing AI “hallucinations.”
• Creating and Editing a New Topic
  Design structured conversation flows that guide your Copilot’s responses with accuracy and intent.
• Getting Our Copilot to Perform Actions
  Add real-world functionality like fetching data, triggering automations, or integrating with your tech stack.
• Activity, Analytics, and Channels
  Track performance with analytics and deploy your Copilot to Microsoft Teams, websites, and more.
• Testing Agents in Copilot Studio
  Debug and simulate real user interactions to refine your Copilot before launch.
• Publishing Our Agent
  Wrap up the course by publishing your Copilot for real-world use across your preferred channels.

Prepare your team to start building their first Copilots!
Check out Introduction to Copilot Studio today and see how no-code AI can transform workflows.